The field of the disclosure is magnetic resonance imaging (“MRI”) systems and methods. More particularly, the disclosure relates to systems and methods for improved correction of MR images for intrinsic heterogeneity.
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the excited nuclei in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) that is in the x-y plane and that is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mt. A signal is emitted by the excited nuclei or “spins,” after the excitation signal B1 is terminated, and this signal may be received and processed to form an image.
In MRI systems, the excited spins induce an oscillating sine wave signal in a receiving coil. The frequency of this signal is near the Larmor frequency, and its initial amplitude, A0, is determined by the magnitude of the transverse magnetic moment Mt. The amplitude, A, of the emitted NMR signal decays in an exponential fashion with time, t. The decay constant 1/T*2 depends on the homogeneity of the magnetic field and on T2, which is referred to as the “spin-spin relaxation” constant, or the “transverse relaxation” constant. The T2 constant is inversely proportional to the exponential rate at which the aligned precession of the spins would dephase after removal of the excitation signal B1 in a perfectly homogeneous field. The practical value of the T2 constant is that tissues have different T2 values and this can be exploited as a means of enhancing the contrast between such tissues.
Another important factor that contributes to the amplitude A of the NMR signal is referred to as the spin-lattice relaxation process that is characterized by the time constant T1. It describes the recovery of the net magnetic moment M to its equilibrium value along the axis of magnetic polarization (z). The T1 time constant is longer than T2, much longer in most substances of medical interest. As with the T2 constant, the difference in T1 between tissues can be exploited to provide image contrast.
Thus, images weighted based on the T1 or T2 time constants can be referred to as relaxation weighted imaging; however, a variety of other contrast mechanisms have also been developed. For example, a so-called diffusion weighted imaging (DWI) pulse sequence uses motion sensitizing magnetic field gradients to obtain images having contrast related to the diffusion of water or other fluid molecules. Specifically, a DWI pulse sequence applies diffusion sensitizing magnetic field gradients in selected directions during the MRI measurement cycle to obtain MR images that have an image contrast related to the diffusion of water or other fluid molecules that occurred during the application of the diffusion gradients. Using these DWI images, an apparent diffusion coefficient (ADC) may be calculated for each voxel location in the reconstructed images.
The particular information sought in given clinical application may dictate a desired contrast mechanism (for example, T1 weighting, T2 weighting, diffusion weighting, perfusion imaging, and the like). For example, DWI and its metric, ADC, have been widely used to evaluate subjects after stroke and guide clinical decisions. In addition to DWI and ADC, another MR diffusion metric has been proposed called diffusion kurtosis imaging (DKI). For example, DKI has been used to study brain disorders, assess cerebral infarction, and assess stroke.
In particular, DKI relies upon the knowledge that water diffusion in biological tissues is non-Gaussian and; thus, DKI extends conventional diffusion tensor imaging (DTI) by estimating the non-Gaussianity of the water diffusion probability distribution as reflected by data acquired from a subject. To this end, the “kurtosis” is a dimensionless means through which one can quantify the non-Gaussianity of data. When considering a given set of data, a positive kurtosis indicates that the data is more strongly peaked and has lighter tails than a set of data that matched a Gaussian distribution.
Qualitatively, a large diffusional kurtosis suggests a high degree of diffusional heterogeneity and microstructural complexity. Unfortunately, since DKI is heterogeneous in normal brain, it can be difficult to quantify kurtosis abnormality. As such, when attempting to use DKI for particular clinical applications, such as stroke evaluation, it can be difficult to precisely delineate stroke-induced lesion using DKI.
Thus, it would be desirable to have a system and method for providing improved clinical information using contrast mechanisms, such as DKI or others like chemical exchange saturation transfer (CEST), magnetization transfer (MT), amide proton transfer (APT), images against intrinsic heterogeneity.